(Senior) Data & MLOps Engineer (m/f/d)
(Senior) Data & MLOps Engineer (m/f/d)
(Senior) Data & MLOps Engineer (m/f/d)
(Senior) Data & MLOps Engineer (m/f/d)
Tchibo GmbH
Konsumgüter, Handel
Hamburg
- Art der Anstellung: Vollzeit
- Vor Ort
- Zu den Ersten gehören
(Senior) Data & MLOps Engineer (m/f/d)
Über diesen Job
(Senior) Data & MLOps Engineer (m/f/d)
Datum: 27.08.2025
Standort: Bucharest, Hamburg, DE, 010011
Unternehmen: Tchibo GmbH
Tchibo is one of the ten largest eCommerce companies in Germany. We could never have attained this standing without the courage to constantly rethink the old ways. In the digital world at Tchibo, we work with the latest technologies to develop sustainable and effective solutions. Do you want to help us do this? Enrich our team with your fresh ideas!
Your tasks: You make the difference with us.
This position is located in Bucharest, Romania.
We’re looking for a Senior Data & MLOps Engineer (m/f/d) to join Tchibo’s "Machine Learning & Predictive" team, part of our Data & AI department. You’ll help scale robust, production-ready ML systems and data infrastructure across strategic business areas, enabling our data-driven transformation. We design, build, and operate innovative ML services for sales and logistics, and provide end-to-end support as trusted advisors across the organization. This role reinforces our MLOps capabilities to meet growing demand, enhance deployment, and ensure operational excellence for our Data Science teams.
- Develop and enhance the MLOps framework and drive adoption across ML projects
- Build and maintain ETL/ML pipelines using GCP services, Airflow, and orchestration tools
- Implement CI/CD processes and GitLab pipelines for automated ML deployments
- Manage infrastructure with Terraform, Docker, and cloud-native GCP services
- Provide technical support to Data Science teams on MLOps/DevOps practices
- Monitor and optimize production ML systems for stability, performance, and scalability
- Develop and integrate APIs to enable seamless data flow and model serving
- Collaborate with cross-functional teams to advance ML system maturity and operational excellence
- Design and maintain robust ML infrastructure and data pipeline architectures
- Enhance maturity, stability, and maintainability of ML systems to support scalable growth
Your profile: You keep reinventing us.
- Bachelor’s/Master’s in Computer Science, Software Engineering, or related field
- 3–5+ years in Data Engineering, MLOps or DevOps
- Experienced in agile methodologies and cross-functional collaboration
- Strong in data processing, ETL, and ML pipeline development/orchestration
- Proficient in Python & SQL (clean code principles)
- Hands-on with GitLab CI/CD, CI components, and automated pipelines
- Deep expertise in GCP: GCS, BigQuery, CloudRun, VertexAI
- Skilled in Docker, dev-containers, and microservices
- Proficient with Terraform, dbt, and Airflow orchestration
- Experienced in API development & modern DevOps practices
- Collaborative, service-oriented team player supporting Data Science teams
- Pragmatic problem-solver balancing technical and business needs
- Strategic thinker with oversight in complex technical landscapes
- Self-driven, organized, able to manage multiple priorities
- Fully proficient in English; German preferred
Your benefits: Together we stay different.
- Work-Life Balance: Flexible hybrid working policy, 26 vacation days + your birthday off.
- Perks: Monthly transport allowance, meal tickets, health & life insurance.
- Coffee Lovers Welcome: Free Tchibo coffee for home and office.
- Innovative Work Culture: You’ll work on impactful projects in a collaborative and open-minded team.
- Diversity & Inclusion: A place where your perspectives and ideas are valued.
Ready to unlock the power of data at Tchibo? Join us and make an impact that goes beyond numbers! Your contact person is Maria Manu , maria.manu@tchibo.ro
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Unternehmenskultur
Unternehmenskultur
2050 Mitarbeitende haben abgestimmt: Sie bewerten die Unternehmenskultur bei Tchibo GmbH als eher traditionell.Dies stimmt ungefähr mit dem Branchen-Durchschnitt überein.